Content area

Abstract

The convergence of digital twin technology and data analytics continues in the area of smart cities focusing on the comprehensive study of data analysis and its visualization. It begins by standing a foundational framework for data analytics and discussing the importance of these ideas in figuring out complex patterns, concluding, and supporting thoughtful decision-making. The article emphasizes the crucial role of data analytics for urban innovation in the context of smart cities using digital twins. The study delves into the complexities of data collection, integration challenges, and innovative solutions, underscoring the necessity of constructing a robust digital twin ecosystem with a variety of sensors and data sources with its visualization. Smart recommendations by monitoring, prescriptive, and real-time analytics are becoming essential tools for vigilant urban management for taking the best and next course of action. The article delves into predictive analytics, highlighting the synergy of data streams for a comprehensive understanding of urban dynamics.

Details

10000008
Title
Leveraging AI and Machine Learning for Enhanced Data Analytics and Visualization in Database Management With Digital Twins
Author
Chui, Kwok Tai 1 ; Singh, Sunil K. 2 ; Kumar, Sudhakar 2 ; Attar, Razaz Waheeb 3 ; Alhomoud, Ahmed 4 ; Goyal, Shivam 2 ; Arya, Varsha 5 ; Gupta, Brij B. 6 

 Hong Kong Metropolitan University, Hong Kong, China 
 Chandigarh College of Engineering and Technology, Panjab University, Chandigarh, India 
 Management Department, College of Business Administration, Princess Nourah bint Abdulrahman University, Saudi Arabia 
 Department of Computer Science, College of Science, Northern Border University, Arar, Saudi Arabia 
 Hong Kong Metropolitan University, Hong Kong, China & UCRD, Chandigarh University, Chandigarh, India, & Center for Interdisciplinary Research, University of Petroleum and Energy Studies (UPES), Dehradun, India 
 Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan, & Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan, & Symbiosis Centre for Information Technology (SCIT), Symbiosis International University, Pune, India, & School of Cybersecurity, Korea University, Seoul, South Korea 
Publication title
Volume
36
Issue
1
Pages
1-29
Number of pages
30
Publication year
2025
Publication date
2025
Publisher
IGI Global
Place of publication
Hershey
Country of publication
United States
ISSN
10638016
e-ISSN
15338010
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Milestone dates
2025-01-01 (pubdate)
ProQuest document ID
3255275730
Document URL
https://www.proquest.com/scholarly-journals/leveraging-ai-machine-learning-enhanced-data/docview/3255275730/se-2?accountid=208611
Copyright
© 2025. This work is published under https://creativecommons.org/licenses/by/4.0/ (the "License").  Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-12-15
Database
ProQuest One Academic